Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals

Rivera Campoverde Néstor Diego; Paúl Andrés Molina Campoverde; Gina Pamela Quirola Novillo; Andrea Karina Naula Bermeo

doi:10.1007/978-3-030-59194-6_11

Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals

Rivera Campoverde Néstor Diego
, Paúl Andrés Molina Campoverde
, Gina Pamela Quirola Novillo
, Andrea Karina Naula Bermeo

Grupo de Investigación en Ingeniería del Transporte (GIIT)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

5 Citas (Scopus)

Resumen

The present project shows an algorithm capable of visualizing the behavior of the PID signals of a vehicle by identifying common driving maneuvers such as: starting, changing gear and engine braking during a road test. The data of this study were acquired through the OBD-II connector of a vehicle, by means of a data logger device capable of collecting the information and writing it to a data file. Later the data is post processed in MATLAB® using the unsupervised learning method k-means. Finally, the results obtained by the algorithm are able to discriminate the erroneous values of the signals by means of a multivariate statistical analysis that classifies the study variables: start, gear change and engine brake.

Idioma original	Inglés
Título de la publicación alojada	Systems and Information Sciences - Proceedings of ICCIS 2020
Editores	Miguel Botto-Tobar, Willian Zamora, Johnny Larrea Plúa, José Bazurto Roldan, Alex Santamaría Philco
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	121-133
Número de páginas	13
ISBN (versión impresa)	9783030591939
DOI	https://doi.org/10.1007/978-3-030-59194-6_11
Estado	Publicada - 2021
Evento	1st International Conference on Systems and Information Sciences, ICCIS 2020 - Manta, Ecuador Duración: 27 jul. 2020 → 29 jul. 2020

Serie de la publicación

Nombre	Advances in Intelligent Systems and Computing
Volumen	1273 AISC

Conferencia

Conferencia	1st International Conference on Systems and Information Sciences, ICCIS 2020
País/Territorio	Ecuador
Ciudad	Manta
Período	27/07/20 → 29/07/20

Nota bibliográfica

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Areas de Conocimiento del CACES

617A Diseño y construcción de vehículos, barcos y aeronaves motorizadas

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10.1007/978-3-030-59194-6_11

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Néstor Diego, R. C., Molina Campoverde, P. A., Quirola Novillo, G. P., & Naula Bermeo, A. K. (2021). Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals. En M. Botto-Tobar, W. Zamora, J. Larrea Plúa, J. Bazurto Roldan, & A. Santamaría Philco (Eds.), Systems and Information Sciences - Proceedings of ICCIS 2020 (pp. 121-133). (Advances in Intelligent Systems and Computing; Vol. 1273 AISC). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59194-6_11

Néstor Diego, Rivera Campoverde ; Molina Campoverde, Paúl Andrés ; Quirola Novillo, Gina Pamela et al. / Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals. Systems and Information Sciences - Proceedings of ICCIS 2020. editor / Miguel Botto-Tobar ; Willian Zamora ; Johnny Larrea Plúa ; José Bazurto Roldan ; Alex Santamaría Philco. Springer Science and Business Media Deutschland GmbH, 2021. pp. 121-133 (Advances in Intelligent Systems and Computing).

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title = "Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals",

abstract = "The present project shows an algorithm capable of visualizing the behavior of the PID signals of a vehicle by identifying common driving maneuvers such as: starting, changing gear and engine braking during a road test. The data of this study were acquired through the OBD-II connector of a vehicle, by means of a data logger device capable of collecting the information and writing it to a data file. Later the data is post processed in MATLAB{\textregistered} using the unsupervised learning method k-means. Finally, the results obtained by the algorithm are able to discriminate the erroneous values of the signals by means of a multivariate statistical analysis that classifies the study variables: start, gear change and engine brake.",

keywords = "Engine brake, Gear change, k-means, OBD II, Start",

author = "\{N{\'e}stor Diego\}, \{Rivera Campoverde\} and \{Molina Campoverde\}, \{Pa{\'u}l Andr{\'e}s\} and \{Quirola Novillo\}, \{Gina Pamela\} and \{Naula Bermeo\}, \{Andrea Karina\}",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 1st International Conference on Systems and Information Sciences, ICCIS 2020 ; Conference date: 27-07-2020 Through 29-07-2020",

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Néstor Diego, RC, Molina Campoverde, PA, Quirola Novillo, GP & Naula Bermeo, AK 2021, Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals. En M Botto-Tobar, W Zamora, J Larrea Plúa, J Bazurto Roldan & A Santamaría Philco (eds.), Systems and Information Sciences - Proceedings of ICCIS 2020. Advances in Intelligent Systems and Computing, vol. 1273 AISC, Springer Science and Business Media Deutschland GmbH, pp. 121-133, 1st International Conference on Systems and Information Sciences, ICCIS 2020, Manta, Ecuador, 27/07/20. https://doi.org/10.1007/978-3-030-59194-6_11

Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals. / Néstor Diego, Rivera Campoverde; Molina Campoverde, Paúl Andrés; Quirola Novillo, Gina Pamela et al.
Systems and Information Sciences - Proceedings of ICCIS 2020. ed. / Miguel Botto-Tobar; Willian Zamora; Johnny Larrea Plúa; José Bazurto Roldan; Alex Santamaría Philco. Springer Science and Business Media Deutschland GmbH, 2021. p. 121-133 (Advances in Intelligent Systems and Computing; Vol. 1273 AISC).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

TY - GEN

T1 - Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals

AU - Néstor Diego, Rivera Campoverde

AU - Molina Campoverde, Paúl Andrés

AU - Quirola Novillo, Gina Pamela

AU - Naula Bermeo, Andrea Karina

N1 - Publisher Copyright: © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2021

Y1 - 2021

N2 - The present project shows an algorithm capable of visualizing the behavior of the PID signals of a vehicle by identifying common driving maneuvers such as: starting, changing gear and engine braking during a road test. The data of this study were acquired through the OBD-II connector of a vehicle, by means of a data logger device capable of collecting the information and writing it to a data file. Later the data is post processed in MATLAB® using the unsupervised learning method k-means. Finally, the results obtained by the algorithm are able to discriminate the erroneous values of the signals by means of a multivariate statistical analysis that classifies the study variables: start, gear change and engine brake.

AB - The present project shows an algorithm capable of visualizing the behavior of the PID signals of a vehicle by identifying common driving maneuvers such as: starting, changing gear and engine braking during a road test. The data of this study were acquired through the OBD-II connector of a vehicle, by means of a data logger device capable of collecting the information and writing it to a data file. Later the data is post processed in MATLAB® using the unsupervised learning method k-means. Finally, the results obtained by the algorithm are able to discriminate the erroneous values of the signals by means of a multivariate statistical analysis that classifies the study variables: start, gear change and engine brake.

KW - Engine brake

KW - Gear change

KW - k-means

KW - OBD II

KW - Start

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DO - 10.1007/978-3-030-59194-6_11

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AN - SCOPUS:85094104734

SN - 9783030591939

T3 - Advances in Intelligent Systems and Computing

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EP - 133

BT - Systems and Information Sciences - Proceedings of ICCIS 2020

A2 - Botto-Tobar, Miguel

A2 - Zamora, Willian

A2 - Larrea Plúa, Johnny

A2 - Bazurto Roldan, José

A2 - Santamaría Philco, Alex

PB - Springer Science and Business Media Deutschland GmbH

T2 - 1st International Conference on Systems and Information Sciences, ICCIS 2020

Y2 - 27 July 2020 through 29 July 2020

ER -

Néstor Diego RC, Molina Campoverde PA, Quirola Novillo GP, Naula Bermeo AK. Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals. En Botto-Tobar M, Zamora W, Larrea Plúa J, Bazurto Roldan J, Santamaría Philco A, editores, Systems and Information Sciences - Proceedings of ICCIS 2020. Springer Science and Business Media Deutschland GmbH. 2021. p. 121-133. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-59194-6_11

Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals

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